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Kamlesh Kumar Pandey et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.7, July- 2014, pg. 751-758
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International Journal of Computer Science and Mobile Computing
A Monthly Journal of Computer Science and Information Technology
ISSN 2320–088X
IJCSMC, Vol. 3, Issue. 7, July 2014, pg.751 – 758
RESEARCH ARTICLE
A Comparison and Selection on Basic Type of
Searching Algorithm in Data Structure
Kamlesh Kumar Pandey1, Narendra Pradhan2
¹Computer Science, IGNTU Amarkantak, India
² Computer Science, SS College of Education, Pendra Road, India
1
[email protected]; 2 [email protected]
Abstract— A lot of problems in different practical fields of Computer Science, Database Management System, Networks,
Data Mining and Artificial intelligence. Searching is common fundamental operation and solve to searching problem in a
different formats of these field. This research paper are presents the basic type of searching algorithms of data structure like
linear search, binary search, and hash search. We have try to cover some technical aspects to this searching algorithm. This
research is provides a detailed study of searching algorithms working process, select on Searching Algorithm according To
Problem and compares them on the basis of different parameters like total number of comparison, type of data Structure,
time complexity and space complexity.
Keywords — Sequential Search, Binary Search, Hashing, Hash function, Comparisons, Application, Time Complexity
I. INTRODUCTION
Sorting and Searching are two fundamental operations in a computer science. Sorting means arranging on data in given order
such that increment or decrement. Searching means find out location or find out an element of a given item in a collection of
item. Many data structures are used to store information but Arrays, linked lists and tree are basic data structures used to sorting
and searching operation. Searching element is any type of a numerical data, alphabet, String, character data. A number of
searching algorithms have been developed like that sequential search, binary search, tree search and hashing etc. Every
searching algorithm depends on specific problem, property of data and algorithm complexity. This research paper gives brief
introduction about searching algorithm, we define to which type of searching algorithm used to which type of Problem and we
compare to different type of searching algorithm in a different important parameter like time complexity, space complexity,
associated key, no of comparisons etc. A group of element is originated to a file or table. Each element is a called to recor d.
Search technique is applying to a file or table and find to a specific record with location. Each record is associated to a key and
this key is separated to different record. If key are store on start of a record so this type of key is called to internal key. In other
case key are store on separate table including pointer to the record so this type of key is called external key. Every file or tables
have a two set of key. First set are define a uniquely data this key is a called primary key and this set have an internal and
external key. Second set are define none uniquely data this key is a called secondary key. We search to an element with
location we need to first set after that need to second set.
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Kamlesh Kumar Pandey et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.7, July- 2014, pg. 751-758
The searching technique can be divided into two categories: 1. Internal Searches: - if file or table are kept in main memory
this type of searching is called internal search. 2. External Searches: - if file or table is kept in auxiliary memory (hard disk,
floppy, tape etc) this type of searching is called External Search.
II. WORKING PROCEDURE OF SEARCHING ALGORITHMS
1. Sequential Search:- Simplest form of searching technique is a sequence search or linear search. This search is applicable
to a small size of array or linked list data structure. Find out on searching element in sequential manner on unordered list or
ordered list. In this method searching process are started at begins to end, scans the elements one by one of the list from left to
right until the searching record/element is found. If we taken on ordered list or table then time it given to fast searching and
good efficient as a comparison on unordered list.
Algorithm: Here L is a location variable, I is a variable which value is a element position and A is Array/List[0-N]. SE is
search element.
LINEAR _SEARCH (A,I,SE)
1. Initialize L=0
2. For I=0 to length[A]
//scan on element start to end
3. If (SE = =A [I])
//check on searching element
4. L=L+1
// increment on location variable
5. Return A[I]
//print on finding element
6. END If
7. END For LOOP
8. If L=0 then return “not find out element”
9.Exit
Example:
2. Binary Search: - Another simplest form of searching technique and best efficient method is a binary search. It can be used
if the table is stored as an array and mid size of array. If we use to linked list and insert/delete on data in linked list during
searching time then problem are generated. This algorithm is also based on Divide-and-Conquer algorithm.
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Kamlesh Kumar Pandey et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.7, July- 2014, pg. 751-758
Divide: In sorted list is divided into two parts.
Conquer: We first compare to search/input element with the mid element of the list. If do not match then we check search
element and mid element if search element is less then to mid element then go to first part/left part otherwise go to second/right
part.
Combine: we apply to divide and conquer part whenever our search element is not found. When our search element is found
then list are automatic combined and return.
Algorithm: Here L is a location variable, LOW is start index and HIGHT is last index element position of Sorted Array/List
A[0-N]. SE is search element
BINARY _SEARCH (A,LOW,HIGHT,MID,SE)
1. Initialize LOW=0, HIGHT=N,L=0
2. While(LOW<=HIGHT)
3. MID=(LOW+HIGHT)/2
4. IF (SE==A[MID])
5. L=L+1
6. Return A[MID]
7. Else If(SE<A[MID])
8. HIGHT=MID-1
9. Else
10. LOW=MID+1
11. END If Statement
11. END While LOO
12. If L=0 then return “not find out element”
13. Exit
//scan on element start to end
//divide on list
// check on searching element
// increment on location variable
//print on finding element
// go to Left/first part
// go to right/second part
Example:
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Kamlesh Kumar Pandey et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.7, July- 2014, pg. 751-758
3. Hashing: - Best searching Technique and most efficient method is a hash search. It searches technique whose search times
can be independent of the number of entries in a table. Hashing has a worst-case behavior that is linear for finding a target
value, but with some case, hashing can be dramatically fast in the average-case. With this approach, the position of a particular
entry in the table is determined by the key for every record. This association is realized through the use of a hashing function. If
H is a hash function and K is key, H(K) is called hash of key. So a hash function H(K) transforms a key into an address/hash
table index position. if key is a non integer value then we convert to a integer value. Some hashing function is
1. Division Method (tablesize = prime):- choose a prime number M which are equal to a table size and K is a key. The
hash function H is define as H(K)= K MOD M or H(K)= (K MOD M) +1. First function denotes the remainder
when K is divided by M. second function is used when we want the hash table to range from 1 to M rather than from
0 to M-1.
2. Midsquare Method (tablesize = 2n):- The multiplication method may be used for a HashTableSize that is a power of 2.
In this method a key is multiplied by itself and the address is obtained by selecting a number from the middle of the
square. The hash function H is define as H(K)= L is obtained K2.
3. Folding Method:- in this method key is portioned into a equal number of parts. this part are added together and
ignoring the final carry, to from an address. The hash function H is define as H(K)=K 1+K2+………+Kn
4. Variable string exclusive-or method (tablesize = 256):- To obtain a hash value in the range 0-255, all bytes in the set of
character are exclusive-or together. However, in the process of doing each exclusive-or, a random component is
introduced. The exclusive-or method has its basis in cryptography
Some time hash function given to map several key into the same address this situation is called Collision. And remove this
collision using Buckets and Chaining method.
Algorithm: Many algorithms are use to hashing according to problem. Basically algorithm are divided in four categories
Cyclic Redundancy Checks Algorithm, Checksum Algorithm, Cryptographic hash Algorithm(SECURE HASH ALGORITHM )
and searching on data(Open addressing, Static and dynamic hashing).
Example: Hash Function
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Kamlesh Kumar Pandey et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.7, July- 2014, pg. 751-758
Example: Hashing Process
III. PROBLEM DEFINITION AND SEARCHING ALGORITHM
All searching algorithm are problem specific. In this section we described some problem and analysis which searching
algorithm is more suitable for that problem
TABLE 1:-SEARCHING ALGORITHM ACCORDING TO PROBLRM
Problem Definition
1. Find out a particular value in a small size of data origination
2. Resource Efficient Problem
3. Searching on unsorted data list
4. Find out data at a time, without jumping
1.
2.
3.
4.
5.
Used to access ordered data quickly when memory space is tight
Fast searching in large data origination and mid data origination
Find out path on mixed analog circuits
Maintains a contiguous subsequence of the starting sequence
where the target value is surely located
1.
2.
3.
4.
5.
Constructing Indices
Storage for Object-Oriented Databases
Achieve Authentication and Data Integrity in a Cryptography
Fast searching in large data origination
How to Search documents on the internet for documents similar to a given one
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Searching Algorithm
Sequential Search
Binary Search
Hashing
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Kamlesh Kumar Pandey et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.7, July- 2014, pg. 751-758
IV. COMPARITIVE STUDY OF ALL ALGORITHMS
TABLE 2:- COMPARISONS OF COMPARISON BASED SEARCHING TECHNIQUES ON VARIOUS PARAMETERS
Parameter
Total
no
comparison
of
Sequential Search
Binary Search
Hash Search
(N+1)/2 for successful,
Each comparison reduces the number of
possible candidates by a factor of 2.
approximately comparison is 2*log2N
In double hashing tech.
N for unsuccessful
log(Tablesize+1)-0.5
successful,
for
(Tablesize+1)/2
unsuccessful
for
Time Complexity
1.Best Case
O(1)
O(1)
O(1)
2.Average Case
O(N )
O(log N)
O(1)
3.Worst Case
O(N )
O(log N)
O(N)
Space Complexity
O(N)
O(N)
O(N )
Associated key
Internal key
Internal key
External Key
Searching type
Internal Searches
Internal Searches
External Searches
Sorting
Do not needed, depending
on user
Yes , use to any type of Sorting method
Do not needed, depending on
user
Data Structure
Array, Linked List
Array
Array, Linked
pointer
Simplicity
Easy
Average
Hard
Efficient
Low
Medium
High
Algorithm
Straightforward
Divide-and-Conquer
Cryptographic(SHA,MD5)
and
non
Cryptographic(Dynamic
search) algorithm
Easy
Average
Average implementation to
data
Structure/hard
implementation
to
cryptography
Strategy
Scan on list start to end
and match search element
one by one
Divide on list match on mid element and
search element. If the search element is less
than the middle element, do again searching
on the left half; otherwise, search the right
half.
Location of storage is
computed
using
the
key(search element key) and
a hash function, and direct go
to desired element
Table and file are
Unordered/Ordered
Ordered
Unordered/Ordered
algorithm
Implementation
programming
on
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756
List
and
Kamlesh Kumar Pandey et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.7, July- 2014, pg. 751-758
Size of table/file
Java function
implementation
on
Suitable for small size
Suitable for mid size/large size
Suitable for large size of
No specific function
binarySearch(array,search_key)
hashcode()
V. ADVANTAGE/DISADVANTAGE AND APPLICATION OF SEARCHING ALGORITHM
. In this section we cover some basic Advantage/Disadvantage and Application of searching algorithm which helpful to select
on search algorithm according to our needed.
TABLE 3 ADVANTAGE/DISADVANTAGE OF SEARCHING TECHNIQUES
Advantage
Searching
Techniques
Sequential Search



Binary Search


Hash Search



Disadvantage
For smaller lists linear search may be
faster because the speed of the simple
increment.
Linear search very simplicity,
resource efficient and memory
efficient.
It can operate sorted and unsorted
array and link list.
The general moral is that for large
lists binary search is very much faster
than linear search.
This search technique given a
searching approach on binary search
tree and other tree.

Searching is faster and more efficient
in large list as compares to other
searching algorithm.
More reliable and flexible of data
retrieval then other Data Structure.
Various type of Hashing Algorithm
is use to different filed of computer.
Hashing use in network security for
Authentication and Data Integrity

Linear search technique is low
efficient and slower than other
searching algorithm.
Not suitable for large data set.


Binary search is not appropriate
for linked list structures (no
random access for the middle
term)
Apply searching before we needed
searching Algorithm.
Not suitable for inserted/deleted a
data in a searching time as a
compare to other searching
algorithm.
Hash function and key are must be
needed.
Large Memory size is required.
Some time hash function given to
same index in hash index table in
different key. Then time we
needed a collision remove
technique.





It is not efficient in a small Hash
Table.
TABLE 4:- APPLICATION OF SEARCHING ALGORITHM
Sequential Search




Index
sequential
search
implementations
Recognition system
Analysis to Hacking system
Phonebook
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Binary Search



Binary search Tree/Tree search
implementations
Microprocessor and many
analog mixed signal circuits
3D games
Hash Search
Application of Hashing


Construction on symbol table
for compiler
Accessing tree or graph nodes
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Kamlesh Kumar Pandey et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.7, July- 2014, pg. 751-758




Cable and Telephone Networks
for Data Transmission
Address Mapping in computer
network
Find out an object in a rasterscan system display.
Checking for spell-checking





Number guessing game
Searching a telephone book
Packing rectangles
Prefix search
Client
and
server
communication


by name
Maintain a transposition table
in games
Dictionary lookups
Application of Hash function




Construction
on
message
authentication code(MAC)
Use to digital signature
Cryptography
Time stamping
VI. CONCLUSIONS
This paper discusses three basic type of searching algorithms and their example. Searching is the process to finding to location
of The given data elements in the data structure. Hashing are faster for large lists as a compare Binary search and Binary search
are faster for mid size lists or small list as a compare Linear search. We have compared the searching algorithm on the basis of
various factors like complexity, data structure, searching type, application etc. we introduced which type of problem solve
through which type of searching algorithm it help to selection on best searching algorithm.
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